docs: def L(s, o, N=5):
      """
          Likelihood
          input:
          s: simulated
          o: observed
          output:
          L: likelihood
          """
      # s,o = filter_nan(s,o)
      return np.exp(-N*np.sum((s-o)**2)/np.sum((o-np.mean(o))**2))